{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# fitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.interpolate import interp1d\n",
    "%matplotlib inline\n",
    "#创建待插值的数据\n",
    "x = np.linspace(0, 4*np.pi, 10)\n",
    "y = np.cos(x)\n",
    "# 分别用linear和quadratic插值\n",
    "fl = interp1d(x, y, kind='linear') # xy为已知点\n",
    "fq = interp1d(x, y, kind='quadratic')\n",
    "\n",
    "#设置x的最大值和最小值以防止插值数据越界\n",
    "xint = np.linspace(x.min(), x.max(), 1000)\n",
    "yintl = fl(xint) #根据拟合函数f1 球的 拟合点y\n",
    "yintq = fq(xint)\n",
    "import pylab as pl\n",
    "pl.plot(xint,fl(xint), color=\"green\", label = \"Linear\")\n",
    "pl.plot(xint,fq(xint), color=\"yellow\", label =\"Quadratic\")\n",
    "pl.legend(loc = \"best\")\n",
    "pl.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
